R: geom_point - how to show statistics on top of figure - r

Question

I made a figure using geom_point from ggplot2 (just showing part of it). Colors are representing 3 classes. Black bar is mean (not relevant for the question).
The data structure is the following (stored in a list):
V1 V2 V3
1 L. brevis 5 class1
3 L. sp. 13 class1
4 L. rhamnosus 14 class1
5 L. lindneri 17 class1
6 L. plantarum 17 class1
7 L. acidophilus 18 class1
8 L. acidophilus 18 class1
10 L. plantarum 18 class1
... ... .. ...
Where V2 is the position of the datapoints on the y-axis and V3 is the class (color).
Now I would like to show the percentages for each of the three classes on top of the figure (Or maybe even as pie charts :-) ). I made an example for "L. acidophilus" on the image (66.7% / 33.3%).
The legend explaining groups ideally is also produced by R but I can do it manually.
How do I do that?
Forgot to add the 0% for group three on top of column "L. acidophilus"... Sorry for that.
EDIT: Here the ggplot2 code:
p <- ggplot(myData, aes(x=V1, y=V2)) +
geom_point(aes(color=V3, fill=V3), size=2.5, cex=5, shape=21, stroke=1) +
scale_color_manual(values=colBorder, labels=c("Class I","Class II","Class III","This study")) +
scale_fill_manual(values=col, labels=c("Class I","Class II","Class III","This study")) +
theme_bw() +
theme(axis.text.x=element_text(angle=50,hjust=1,face="italic", color="black"), text = element_text(size=12),
axis.text.y=element_text(color="black"), panel.grid.major = element_line(color="gray85",size=.15), panel.grid.minor = element_blank(),
panel.grid.major.y = element_blank(), axis.ticks = element_line(size = 0.3), panel.border = element_rect(fill=NA, colour = "black", size=0.3)) +
stat_summary(aes(shape="mean"), fun.y=mean, size = 6, shape=95, colour="black", geom="point") +
guides(fill=guide_legend(title="Class", order=1), color=guide_legend(title="Class",order=1), shape=guide_legend(title="Blup", order=2))

Answer 1

Option A: Secondary Axis
You can do this using a secondary x axis (new to ggplot2 v2.2.0), but it's hard to do with a categorical variable on the x axis because it doesn't work with scale_x_discrete(), only scale_x_continuous(). So, you have to convert the factor to integer, plot based on that, and then overwrite the labels on the primary x axis.
For example:
set.seed(123)
df <- iris[sample.int(nrow(iris),size=300,replace=TRUE),]
# Assume we are grouping by species
# Some group-level stats -- how about count and mean/sdev of sepal length
library(dplyr)
df_stats <- df %>%
group_by(Species) %>%
summarize(stat_txt = paste0(c('N=','avg=','sdev='),
c(n(),round(mean(Sepal.Length),2),round(sd(Sepal.Length),3) ),
collapse='\n') )
library(ggplot2)
ggplot(data = df,
aes(x = as.integer(Species),
y = Sepal.Length)) +
geom_point() +
stat_summary(aes(shape="mean"), fun.y=mean, size = 6, shape=95,
colour="black", geom="point") +
theme_bw() +
scale_x_continuous(breaks=1:length(levels(df$Species)),
limits = c(0,length(levels(df$Species))+1),
labels = levels(df$Species),
minor_breaks=NULL,
sec.axis=sec_axis(~.,
breaks=1:length(levels(df$Species)),
labels=df_stats$stat_txt)) +
xlab('Species') +
theme(axis.text.x = element_text(hjust=0))
Option B: grid.arrange your statistics as a separate chart atop your main chart.
This is a little more straightforward, but the two charts don't quite perfectly line up, possibly because of the ticks and labels being suppressed on the axes of the top chart.
library(ggplot2)
library(gridExtra)
p <-
ggplot(data = df,
aes(x = Species,
y = Sepal.Length)) +
geom_point() +
stat_summary(aes(shape="mean"), fun.y=mean, size = 6, shape=95,
colour="black", geom="point") +
theme_bw() +
theme(axis.text.x = element_text(angle=45, hjust=1, vjust=1))
annot <-
ggplot(data=df_stats, aes(x=Species, y = 0)) +
geom_text(aes(label=stat_txt), hjust=0) +
theme_minimal() +
scale_x_discrete(breaks=NULL) +
scale_y_continuous(breaks=NULL) +
xlab(NULL) + ylab('')
grid.arrange(annot, p, heights=c(1,8))